May 2021
Beginner to intermediate
380 pages
9h 22m
Korean
Content preview from 데이터 과학을 위한 통계(2판)
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350
데이터 과학을 위한 통계
주요 개념
• 모든 레코드를 각각 자체 클러스터로 할당하여 계층적 클러스터링 알고리즘을 시작한다.
• 클러스터들은 모든 레코드가 하나의 클러스터에 속할 때까지 가까운 클러스터와 계속해서 연결된다 (병합
알고리즘 ).
• 병합 과정은 내역이 남고 시각화할 수 있으며, 사용자가 미리 클러스터 수를 지정하지 않더라도 여러 단계
에서 클러스터의 수와 구조를 시각화할 수 있다.
• 클러스터 간 거리는 모든 레코드 간 거리 정보를 사용하여 여러 가지 다른 방식으로 계산할 수 있다.
7.4
모델 기반 클러스터링
계층적 클러스터링과
k
-평균 같은 클러스터링 방법들은 모두 휴리스틱한 방법
heuristic
이라고 할
수 있으며, 직접 관측한 (즉 확률모형에 기반하지 않고) 데이터들이 서로 가깝게 있는 클러스
터를 찾는 데 주로 사용된다. 연구자들은 지난
20
년간
모델 기반 클러스터링
model
-
based
clustering
을
개발하는 데 많은 노력을 기울여왔다. 워싱턴 대학교의 에이드리언 래프터리
Adrian
Raftery
와 동료
들은 이론적인 측면과 소프트웨어적인 측면에서 모델 기반 클러스터링을 개발하는 데 큰 기여
를 했다. 이 기법은 통계 이론에 기초하고 있으며 클러스터의 성질과 수를 결정하는 더 엄격한
방법을 제공한다. 예를 들면 전반적으로는 ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.